Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations2969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory278.3 KiB
Average record size in memory96.0 B

Variable types

Numeric11

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticketHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
invoice_no is highly overall correlated with gross_revenue and 2 other fieldsHigh correlation
quantity is highly overall correlated with avg_basket_size and 2 other fieldsHigh correlation
recency_days is highly overall correlated with invoice_noHigh correlation
avg_ticket is highly skewed (γ1 = 53.4442279) Skewed
avg_basket_size is highly skewed (γ1 = 44.68328098) Skewed
customer_id has unique values Unique
recency_days has 34 (1.1%) zeros Zeros
qtde_returns has 1481 (49.9%) zeros Zeros

Reproduction

Analysis started2025-04-07 14:33:45.381835
Analysis finished2025-04-07 14:34:15.713568
Duration30.33 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.773
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:15.917796image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.4
Q113799
median15221
Q316768
95-th percentile17964.6
Maximum18287
Range5940
Interquartile range (IQR)2969

Descriptive statistics

Standard deviation1718.9903
Coefficient of variation (CV)0.11256734
Kurtosis-1.2060947
Mean15270.773
Median Absolute Deviation (MAD)1488
Skewness0.031607859
Sum45338925
Variance2954927.6
MonotonicityNot monotonic
2025-04-07T11:34:16.247141image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
17588 1
 
< 0.1%
14905 1
 
< 0.1%
16103 1
 
< 0.1%
14626 1
 
< 0.1%
14868 1
 
< 0.1%
18246 1
 
< 0.1%
17115 1
 
< 0.1%
16611 1
 
< 0.1%
15912 1
 
< 0.1%
Other values (2959) 2959
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2954
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.2261
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:16.552151image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.77
Q1570.96
median1086.92
Q32308.06
95-th percentile7219.68
Maximum279138.02
Range279131.82
Interquartile range (IQR)1737.1

Descriptive statistics

Standard deviation10580.491
Coefficient of variation (CV)3.8485342
Kurtosis353.95857
Mean2749.2261
Median Absolute Deviation (MAD)672.72
Skewness16.777879
Sum8162452.2
Variance1.1194678 × 108
MonotonicityNot monotonic
2025-04-07T11:34:16.871874image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178.96 2
 
0.1%
533.33 2
 
0.1%
889.93 2
 
0.1%
2053.02 2
 
0.1%
745.06 2
 
0.1%
379.65 2
 
0.1%
2092.32 2
 
0.1%
731.9 2
 
0.1%
1353.74 2
 
0.1%
331 2
 
0.1%
Other values (2944) 2949
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

High correlation  Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.288649
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:17.192437image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.756171
Coefficient of variation (CV)1.2094852
Kurtosis2.7780386
Mean64.288649
Median Absolute Deviation (MAD)26
Skewness1.7983969
Sum190873
Variance6046.0221
MonotonicityNot monotonic
2025-04-07T11:34:17.529456image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
2 85
 
2.9%
3 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
22 55
 
1.9%
Other values (262) 2219
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

invoice_no
Real number (ℝ)

High correlation 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7228023
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:17.877544image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8566539
Coefficient of variation (CV)1.5476079
Kurtosis190.82536
Mean5.7228023
Median Absolute Deviation (MAD)2
Skewness10.766456
Sum16991
Variance78.440319
MonotonicityNot monotonic
2025-04-07T11:34:18.201510image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 786
26.5%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 786
26.5%
3 498
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

quantity
Real number (ℝ)

High correlation 

Distinct48
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.621421
Minimum1
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:18.528088image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median11
Q314
95-th percentile22
Maximum102
Range101
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.2631661
Coefficient of variation (CV)0.53893288
Kurtosis25.435157
Mean11.621421
Median Absolute Deviation (MAD)3
Skewness3.1042989
Sum34504
Variance39.22725
MonotonicityNot monotonic
2025-04-07T11:34:18.859481image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
10 288
 
9.7%
9 262
 
8.8%
11 255
 
8.6%
12 220
 
7.4%
8 217
 
7.3%
7 212
 
7.1%
13 199
 
6.7%
14 165
 
5.6%
6 157
 
5.3%
15 138
 
4.6%
Other values (38) 856
28.8%
ValueCountFrequency (%)
1 19
 
0.6%
2 32
 
1.1%
3 60
 
2.0%
4 82
 
2.8%
5 105
 
3.5%
6 157
5.3%
7 212
7.1%
8 217
7.3%
9 262
8.8%
10 288
9.7%
ValueCountFrequency (%)
102 1
 
< 0.1%
74 1
 
< 0.1%
58 2
0.1%
57 1
 
< 0.1%
56 1
 
< 0.1%
54 1
 
< 0.1%
50 2
0.1%
49 3
0.1%
44 4
0.1%
43 1
 
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2966
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.900057
Minimum2.1505882
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:19.176877image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.9166611
Q113.119333
median17.974384
Q324.988286
95-th percentile90.497
Maximum56157.5
Range56155.349
Interquartile range (IQR)11.868952

Descriptive statistics

Standard deviation1036.9343
Coefficient of variation (CV)19.979445
Kurtosis2890.7074
Mean51.900057
Median Absolute Deviation (MAD)5.9942223
Skewness53.444228
Sum154091.27
Variance1075232.8
MonotonicityNot monotonic
2025-04-07T11:34:19.493241image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
0.1%
4.162 2
 
0.1%
14.47833333 2
 
0.1%
18.15222222 1
 
< 0.1%
13.92736842 1
 
< 0.1%
36.24411765 1
 
< 0.1%
29.78416667 1
 
< 0.1%
22.8792623 1
 
< 0.1%
20.51104167 1
 
< 0.1%
149.025 1
 
< 0.1%
Other values (2956) 2956
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.35143
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:19.822407image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q125.928571
median48.285714
Q385.333333
95-th percentile201
Maximum366
Range365
Interquartile range (IQR)59.404762

Descriptive statistics

Standard deviation63.542829
Coefficient of variation (CV)0.94345182
Kurtosis4.8877032
Mean67.35143
Median Absolute Deviation (MAD)26.285714
Skewness2.062909
Sum199966.4
Variance4037.6912
MonotonicityNot monotonic
2025-04-07T11:34:20.164044image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 25
 
0.8%
4 22
 
0.7%
70 21
 
0.7%
7 20
 
0.7%
35 19
 
0.6%
49 18
 
0.6%
21 17
 
0.6%
46 17
 
0.6%
11 17
 
0.6%
1 16
 
0.5%
Other values (1248) 2777
93.5%
ValueCountFrequency (%)
1 16
0.5%
1.5 1
 
< 0.1%
2 13
0.4%
2.5 1
 
< 0.1%
2.601398601 1
 
< 0.1%
3 15
0.5%
3.321428571 1
 
< 0.1%
3.330357143 1
 
< 0.1%
3.5 2
 
0.1%
4 22
0.7%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

High correlation 

Distinct1350
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.063271723
Minimum0.0054495913
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:20.524966image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0094339623
Q10.017777778
median0.029411765
Q30.055401662
95-th percentile0.22222222
Maximum3
Range2.9945504
Interquartile range (IQR)0.037623884

Descriptive statistics

Standard deviation0.13448193
Coefficient of variation (CV)2.1254666
Kurtosis121.55969
Mean0.063271723
Median Absolute Deviation (MAD)0.014338235
Skewness8.7734265
Sum187.85375
Variance0.01808539
MonotonicityNot monotonic
2025-04-07T11:34:20.857594image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1666666667 21
 
0.7%
0.3333333333 21
 
0.7%
0.02777777778 20
 
0.7%
0.09090909091 19
 
0.6%
0.0625 17
 
0.6%
0.1333333333 16
 
0.5%
0.4 16
 
0.5%
0.25 15
 
0.5%
0.02380952381 15
 
0.5%
0.03571428571 15
 
0.5%
Other values (1340) 2794
94.1%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
2 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.5 3
 
0.1%
1 14
0.5%
0.8333333333 1
 
< 0.1%
0.75 1
 
< 0.1%
0.6666666667 12
0.4%
0.6514745308 1
 
< 0.1%
0.6 1
 
< 0.1%

qtde_returns
Real number (ℝ)

Zeros 

Distinct21
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2869653
Minimum0
Maximum26
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:21.150715image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1729085
Coefficient of variation (CV)1.6883971
Kurtosis20.392585
Mean1.2869653
Median Absolute Deviation (MAD)1
Skewness3.586371
Sum3821
Variance4.7215315
MonotonicityNot monotonic
2025-04-07T11:34:21.430056image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 1481
49.9%
1 639
21.5%
2 357
 
12.0%
3 198
 
6.7%
4 106
 
3.6%
5 53
 
1.8%
6 37
 
1.2%
7 31
 
1.0%
8 17
 
0.6%
9 12
 
0.4%
Other values (11) 38
 
1.3%
ValueCountFrequency (%)
0 1481
49.9%
1 639
21.5%
2 357
 
12.0%
3 198
 
6.7%
4 106
 
3.6%
5 53
 
1.8%
6 37
 
1.2%
7 31
 
1.0%
8 17
 
0.6%
9 12
 
0.4%
ValueCountFrequency (%)
26 1
 
< 0.1%
21 2
 
0.1%
19 1
 
< 0.1%
18 1
 
< 0.1%
17 2
 
0.1%
16 1
 
< 0.1%
14 5
0.2%
13 2
 
0.1%
12 7
0.2%
11 7
0.2%

avg_basket_size
Real number (ℝ)

High correlation  Skewed 

Distinct1973
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.34954
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:21.740015image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.25
median172
Q3281.5
95-th percentile599.52
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.25

Descriptive statistics

Standard deviation791.50241
Coefficient of variation (CV)3.1742686
Kurtosis2256.2455
Mean249.34954
Median Absolute Deviation (MAD)82.75
Skewness44.683281
Sum740318.79
Variance626476.07
MonotonicityNot monotonic
2025-04-07T11:34:22.157663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
73 9
 
0.3%
86 9
 
0.3%
82 9
 
0.3%
136 8
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
88 8
 
0.3%
71 7
 
0.2%
Other values (1963) 2882
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct1010
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.155074
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-04-07T11:34:22.490155image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3454545
Q110
median17.2
Q327.75
95-th percentile56.94
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.513033
Coefficient of variation (CV)0.88074783
Kurtosis27.694698
Mean22.155074
Median Absolute Deviation (MAD)8.2
Skewness3.4982521
Sum65778.414
Variance380.75846
MonotonicityNot monotonic
2025-04-07T11:34:22.825673image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 53
 
1.8%
14 40
 
1.3%
11 38
 
1.3%
20 33
 
1.1%
9 33
 
1.1%
1 32
 
1.1%
18 31
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
17 28
 
0.9%
Other values (1000) 2622
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

Interactions

2025-04-07T11:34:11.967109image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:46.107045image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:48.989961image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:51.539560image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:54.048129image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:56.461962image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:58.971988image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:01.747101image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:04.269152image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:06.862000image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:09.340662image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:12.539332image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:46.398031image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:49.238830image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:51.761642image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:54.249870image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:56.690839image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:59.190151image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:01.984830image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:04.481107image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:07.090210image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:09.572012image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:12.808875image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:46.623221image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:49.454620image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:51.981906image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:54.454068image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:56.914626image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:59.704013image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:02.220244image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:04.699324image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:07.307029image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:09.808075image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:13.048157image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:46.843794image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:49.690662image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:52.217084image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:54.678186image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:57.145237image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:59.944778image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:02.459742image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:04.943664image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:07.535884image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:10.056180image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:13.254964image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:47.034916image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:49.900483image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:52.423611image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:54.868489image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:57.347790image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:00.172118image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:02.673258image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:05.194161image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:07.741423image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:10.269034image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:13.473111image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:47.229170image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:50.119078image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:52.644810image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:55.077168image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:57.596338image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:00.398648image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:02.890221image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:05.419747image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:07.966937image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:10.501185image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:13.700204image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:47.439901image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:50.358935image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:52.863540image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:55.290125image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:57.832102image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:00.603748image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:03.125626image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:05.659492image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:08.188055image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:10.737338image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:13.959626image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:47.678709image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:50.622048image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:53.094502image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:55.563231image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:58.065040image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:00.844325image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:03.356859image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:05.895464image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:08.422677image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:10.992303image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:14.188902image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:47.896183image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:50.870731image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:53.328983image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:55.786663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:58.285189image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:01.064509image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:03.572809image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:06.134798image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:08.667785image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:11.233430image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:14.408535image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:48.108603image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:51.086859image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:53.561680image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:55.994149image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:58.503552image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:01.285863image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:03.791558image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:06.369097image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:08.884921image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:11.469851image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:14.660036image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:48.683903image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:51.322711image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:53.820400image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:56.236180image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:33:58.743240image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:01.526656image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:04.027009image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:06.627739image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:09.129631image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-07T11:34:11.723999image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2025-04-07T11:34:23.072217image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueinvoice_noqtde_returnsquantityrecency_days
avg_basket_size1.000-0.0770.1890.448-0.1230.0570.5760.1010.1980.519-0.098
avg_recency_days-0.0771.000-0.1220.0480.019-0.962-0.248-0.258-0.410-0.1780.108
avg_ticket0.189-0.1221.000-0.611-0.1310.0980.2460.0590.175-0.0760.048
avg_unique_basket_size0.4480.048-0.6111.000-0.007-0.0420.2910.0250.0360.446-0.106
customer_id-0.1230.019-0.131-0.0071.000-0.008-0.0760.025-0.063-0.0070.001
frequency0.057-0.9620.098-0.042-0.0081.0000.1610.1480.3670.109-0.031
gross_revenue0.576-0.2480.2460.291-0.0760.1611.0000.7700.3700.770-0.415
invoice_no0.101-0.2580.0590.0250.0250.1480.7701.0000.2940.660-0.502
qtde_returns0.198-0.4100.1750.036-0.0630.3670.3700.2941.0000.274-0.125
quantity0.519-0.178-0.0760.446-0.0070.1090.7700.6600.2741.000-0.399
recency_days-0.0980.1080.048-0.1060.001-0.031-0.415-0.502-0.125-0.3991.000

Missing values

2025-04-07T11:34:15.008878image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-07T11:34:15.482832image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.06.018.15222235.5000000.4861114.050.9705888.735294
1130473232.5956.09.011.018.90403527.2500000.0487803.0154.44444419.000000
2125836705.382.015.024.028.90250023.1875000.0456993.0335.20000015.466667
313748948.2595.05.08.033.86607192.6666670.0179210.087.8000005.600000
415100876.00333.03.02.0292.0000008.6000000.1363643.026.6666671.000000
5152914623.3025.014.017.045.32647123.2000000.0544414.0150.1428577.285714
6146885630.877.021.024.017.21978618.3000000.07356919.0172.42857115.571429
7178095411.9116.012.023.088.71983635.7000000.0391062.0171.4166675.083333
81531160767.900.091.043.025.5434644.1444440.31550813.0419.71428626.142857
9160982005.6387.07.015.029.93477647.6666670.0243900.087.5714299.571429
customer_idgross_revenuerecency_daysinvoice_noquantityavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
5627177271060.2515.01.011.016.0643946.00.2857141.0645.00000066.0
563717232421.522.02.010.011.70888912.00.1538460.0101.50000018.0
563817468137.0010.02.02.027.4000004.00.4000000.058.0000002.5
564913596697.045.02.010.04.1990367.00.2500000.0203.00000083.0
5655148931237.859.02.014.016.9568492.00.6666670.0399.50000036.5
565912479473.2011.01.08.015.7733334.00.3333334.0382.00000030.0
568014126706.137.03.06.047.0753333.01.0000001.0169.3333335.0
5686135211092.391.03.09.02.5112414.50.3000000.0244.333333145.0
569615060301.848.04.08.02.5153331.02.0000000.065.50000030.0
571512558269.967.01.05.024.5418186.00.2857145.0196.00000011.0